Exploring_Simplecast.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e1970100-3b92-47b6-9013-1527f79e5ccc",
   "metadata": {},
   "outputs": [],
   "source": [
    "from requests_ratelimiter import LimiterSession as Session\n",
    "import json\n",
    "import pandas as pd\n",
    "import ast\n",
    "import datetime as dt\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e24c51c-b4f1-4c08-9dfc-de1b045cb6a6",
   "metadata": {},
   "source": [
    "## Storing and Loading Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc9ecccb-ca89-444e-bcf7-c805f63ee33f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Storing from previous fetches\n",
    "df_downloads.to_feather(\"total_podcast_downloads.feather\")\n",
    "df.to_feather(\"tbp_episodic_downloads.feather\")\n",
    "df_hio.to_feather(\"hio_episodic_downloads.feather\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e717b5e1-2259-423a-881b-511e47520bdc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading from already stored feather\n",
    "df_downloads = pd.read_feather(\"total_podcast_downloads.feather\")\n",
    "df = pd.read_feather(\"tbp_episodic_downloads.feather\")\n",
    "df_hio = pd.read_feather(\"hio_episodic_downloads.feather\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b52aec6-8740-4b27-8802-587a02823a09",
   "metadata": {},
   "source": [
    "## Getting initial podcast and episode info from Simplecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cae9f85d-9c8a-4596-920f-c391627a095d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting up session to be used\n",
    "### NOTE: Simplecast API has a rate limit of 100 requests per minute. The use of the the Session should be set to this\n",
    "bearer = 'eyJhcGlfa2V5IjoiOTQ1YjhkZjViNDY5MjNlM2ZkZjE2NDJjMWI5ZDE2MmQifQ==' # Corey's key\n",
    "# bearer = 'eyJhcGlfa2V5IjoiYzAxMzg3ODhhNmYzOWFmYjQ0MmYxNTFmOWIzMzg1OTIifQ==' # Jessie's key (Doesn't seem to work)\n",
    "\n",
    "session = Session(per_minute=100)\n",
    "session.headers = {'authorization':'Bearer {}'.format(bearer)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "c55977a7-a0a2-416a-9946-890750c12efb",
   "metadata": {},
   "outputs": [],
   "source": [
    "r = session.get('https://api.simplecast.com/podcasts')\n",
    "podcasts = json.loads(r.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "361d77e4-8780-4162-a00c-05dcc9fb29b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "podcast_ids = []\n",
    "for podcast in podcasts['collection']:\n",
    "    podcast_ids.append({\"title\": podcast['title'], \"id\" : podcast['id']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "9f1e7a8d-f618-4eb9-8fae-47c059e4e9ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "podcast_details = []\n",
    "for podcast in podcast_ids:\n",
    "    r = session.get('https://api.simplecast.com/podcasts/{}'.format(podcast[\"id\"]))\n",
    "    res_podcast = json.loads(r.text)\n",
    "    podcast_details.append(res_podcast)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "419dcdb3-afe7-40ff-9be5-b9ba00ad0684",
   "metadata": {},
   "source": [
    "## Get General Podcast Download Analytics\n",
    "#### Updated 2023-01-30 1:00 PM EST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "8718037a-6a6d-4419-8719-70e205b54a03",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a bunch of useful functions to be used when extracting info from JSON into DataFrames\n",
    "def return_id(json_str):\n",
    "    return json_str['id']\n",
    "\n",
    "def return_downloads(json_str):\n",
    "    return json_str['total']\n",
    "\n",
    "def return_pubdate(json_str):\n",
    "    return json_str['feeds']['collection'][0]['published_at']\n",
    "\n",
    "def get_show(title):\n",
    "    if \"Hashing\" in title:\n",
    "        return \"HIO\"\n",
    "    elif \"HIO\" in title:\n",
    "        return \"HIO\"\n",
    "    else:\n",
    "        return \"TBPN\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "5bc1b838-7448-484a-8403-9c28ea3baaa5",
   "metadata": {},
   "outputs": [],
   "source": [
    "podcast_analytics = []\n",
    "for podcast in podcast_ids:\n",
    "    r = session.get('https://api.simplecast.com/analytics/downloads?podcast={}'.format(podcast[\"id\"]))\n",
    "    res_podcast = json.loads(r.text)\n",
    "    podcast_analytics.append({\"show\": podcast['title'], \"analytics\": res_podcast})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "7696216f-102f-4a93-9d6d-80f48b6f3074",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_downloads = pd.DataFrame(podcast_analytics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0792cbe9-7dbb-4f8f-99f5-963c1e9dd137",
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>show</th>\n",
       "      <th>analytics</th>\n",
       "      <th>id</th>\n",
       "      <th>total_downloads</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hashing It Out</td>\n",
       "      <td>{'by_interval': [{'downloads_percent': 0.08178...</td>\n",
       "      <td>b54c0885-7c72-415d-b032-7d294b78d785</td>\n",
       "      <td>269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Bitcoin Podcast</td>\n",
       "      <td>{'by_interval': [{'downloads_percent': 0.0, 'd...</td>\n",
       "      <td>b623b331-ffef-40c4-918d-b35a07ee8729</td>\n",
       "      <td>2063387</td>\n",
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       "                  show                                          analytics  \\\n",
       "0       Hashing It Out  {'by_interval': [{'downloads_percent': 0.08178...   \n",
       "1  The Bitcoin Podcast  {'by_interval': [{'downloads_percent': 0.0, 'd...   \n",
       "\n",
       "                                     id  total_downloads  \n",
       "0  b54c0885-7c72-415d-b032-7d294b78d785              269  \n",
       "1  b623b331-ffef-40c4-918d-b35a07ee8729          2063387  "
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     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "df_downloads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "601fc6c3-f110-409d-9aed-8621dabd4ef5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_downloads['id'] = df_downloads['analytics'].apply(return_id).copy()\n",
    "df_downloads['total_downloads'] = df_downloads['analytics'].apply(return_downloads).copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1059089b-886e-4a31-b299-1ce342128df8",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Get HIO ids and associated download data\n",
    "#### Updated 2023-01-30 1:00 PM EST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0bf85a64-a8b6-4cb5-83b5-15fabbd9a77b",
   "metadata": {},
   "outputs": [],
   "source": [
    "session = requests.Session()\n",
    "session.headers.update({'authorization':'Bearer {}'.format(bearer)})\n",
    "\n",
    "def get_jobs():\n",
    "    url = \"https://api.simplecast.com/podcasts/{}/episodes\".format(podcast_ids[0]['id'] )\n",
    "    first_page = session.get(url).json()\n",
    "    yield first_page\n",
    "        \n",
    "    while first_page['pages']['next'] != None:\n",
    "        first_page = session.get(first_page['pages']['next']['href']).json()\n",
    "        yield first_page\n",
    "\n",
    "pages = [page for page in get_jobs()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8913c811-6242-4217-9696-c76b35218ec0",
   "metadata": {},
   "outputs": [],
   "source": [
    "hio_episode_ids = []\n",
    "for page in pages:\n",
    "    for episode in page['collection']:\n",
    "        hio_episode_ids.append({\"title\": episode['title'], 'id': episode['id']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "85497657-ebc9-4d2f-b62a-9b518c725ccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "for episode in hio_episode_ids:\n",
    "    url = \"https://api.simplecast.com/analytics/downloads?episode={}\".format(episode['id'])\n",
    "    episode_json = session.get(url).json()\n",
    "    hio_episodic_downloads.append({\"title\": episode['title'], \"downloads\":episode_json})\n",
    "                                                                             "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "c573496c-82b1-4724-b506-4eab5feee8e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_hio = pd.DataFrame(hio_episodic_downloads)\n",
    "df_hio['id'] = df_hio['downloads'].apply(return_id).copy()\n",
    "df_hio['total_downloads'] = df_hio['downloads'].apply(return_downloads).copy()\n",
    "df_hio['published_at'] = df_hio['downloads'].apply(return_pubdate).copy()\n",
    "df_hio['show'] = df_hio['title'].apply(get_show).copy()\n",
    "df_hio = df_hio.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dbf58bd-906c-421d-aae6-1e5b39e4d3cc",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Get TBP Episodic ids and associated downloads data\n",
    "#### Updated 2023-01-30 1:00 PM EST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "16793183-0c07-4790-855e-b36e819516f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "session = requests.Session()\n",
    "\n",
    "def get_jobs():\n",
    "    url = \"https://api.simplecast.com/podcasts/{}/episodes\".format(podcast_ids[1]['id'] )\n",
    "    first_page = session.get(url).json()\n",
    "    yield first_page\n",
    "        \n",
    "    while first_page['pages']['next'] != None:\n",
    "        first_page = session.get(first_page['pages']['next']['href'], headers={'authorization':'Bearer {}'.format(bearer)}).json()\n",
    "        yield first_page\n",
    "\n",
    "pages = [page for page in get_jobs()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "df225e9a-e561-444e-8941-dea1730a9d79",
   "metadata": {},
   "outputs": [],
   "source": [
    "tbp_episode_ids = []\n",
    "for page in pages:\n",
    "    for episode in page['collection']:\n",
    "        tbp_episode_ids.append({\"title\": episode['title'], 'id': episode['id']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "46ad35c3-8972-4c64-8975-a20b90e24493",
   "metadata": {},
   "outputs": [],
   "source": [
    "session = requests.Session()\n",
    "\n",
    "tbp_episodic_downloads = []\n",
    "for episode in tbp_episode_ids:\n",
    "    url = \"https://api.simplecast.com/analytics/downloads?episode={}\".format(episode['id'])\n",
    "    episode_json = session.get(url, headers={'authorization':'Bearer {}'.format(bearer)}).json()\n",
    "    tbp_episodic_downloads.append({\"title\": episode['title'], \"downloads\":episode_json})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "336c46df-85fd-4136-abc3-a5ed44d256ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(tbp_episodic_downloads)\n",
    "df['id'] = df['downloads'].apply(return_id).copy()\n",
    "df['total_downloads'] = df['downloads'].apply(return_downloads).copy()\n",
    "df['published_at'] = df['downloads'].apply(return_pubdate).copy()\n",
    "df['show'] = df['title'].apply(get_show).copy()\n",
    "df = df.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c529039e-f6f1-42a7-8e31-3e7d3376aa60",
   "metadata": {},
   "source": [
    "## Print out some Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f4e13e34-5764-46ca-949e-216ff3ed28d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HIO has 330444 downloads over 118 shows for and average of 2800.3728813559323 downloads/show\n",
      "TBP has 1728937 downloads over 891 shows for and average of 1940.4455667789 downloads/show\n"
     ]
    }
   ],
   "source": [
    "hio_total_downloads = df[df['show'] == 'HIO'].total_downloads.sum()\n",
    "hio_num_shows = len(df[df['show'] == 'HIO'].total_downloads)\n",
    "\n",
    "tbp_total_downloads = df[df['show'] == 'TBPN'].total_downloads.sum()\n",
    "tbp_num_shows = len(df[df['show'] == 'TBPN'].total_downloads)\n",
    "\n",
    "\n",
    "print(\"HIO has {} downloads over {} shows for and average of {} downloads/show\".format(hio_total_downloads, hio_num_shows, hio_total_downloads/hio_num_shows))\n",
    "print(\"TBP has {} downloads over {} shows for and average of {} downloads/show\".format(tbp_total_downloads, tbp_num_shows, tbp_total_downloads/tbp_num_shows))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5248e1fe-a8fe-4885-a835-4c4d6b8ac511",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'by_interval': array([{'downloads_percent': 0.52188, 'downloads_total': 489, 'interval': '2023-01-24'},\n",
       "        {'downloads_percent': 0.21131, 'downloads_total': 198, 'interval': '2023-01-25'},\n",
       "        {'downloads_percent': 0.09712, 'downloads_total': 91, 'interval': '2023-01-26'},\n",
       "        {'downloads_percent': 0.07044, 'downloads_total': 66, 'interval': '2023-01-27'},\n",
       "        {'downloads_percent': 0.0555, 'downloads_total': 52, 'interval': '2023-01-28'},\n",
       "        {'downloads_percent': 0.04376, 'downloads_total': 41, 'interval': '2023-01-29'}],\n",
       "       dtype=object),\n",
       " 'feeds': {'collection': array([{'id': '3aa77255-8f97-4da1-97fa-d9a1c6f73850', 'is_primary': True, 'name': 'Default', 'published_at': '2023-01-24T17:00:00Z', 'scheduled_for': None, 'status': 'published'}],\n",
       "        dtype=object)},\n",
       " 'href': 'https://api.simplecast.com/analytics/downloads?episode=7a6f11df-51a1-4812-bc18-a49c33a95ea4',\n",
       " 'id': '7a6f11df-51a1-4812-bc18-a49c33a95ea4',\n",
       " 'interval': 'day',\n",
       " 'total': 937}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.downloads.values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "5db3e986-491c-4134-8fb1-42521c6bed60",
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         "range": [
          0,
          1004.2105263157895
         ],
         "title": {
          "text": "downloads_total"
         },
         "type": "linear"
        }
       }
      },
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "ep_index = 301\n",
    "test = pd.DataFrame([dic for dic in df.downloads.values[ep_index]['by_interval']])\n",
    "test['date'] = pd.to_datetime(test['interval'], infer_datetime_format=True)\n",
    "fig = px.bar(test, y=\"downloads_total\", x='date', title=df.title.values[ep_index] + ' - ' + df.downloads.values[ep_index]['feeds']['collection'][0]['published_at'])\n",
    "fig.show()"
   ]
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   "id": "d1aacbd5-a827-44f5-aec1-d9408b1e49ea",
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   "source": []
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